We are looking for a Senior Software Development Engineer who will own the infrastructure, platform, and production systems that underpin our agentic autonomous campaigns. In this role, you will lead the design, build, and scaling of core services such as tool orchestration, agent execution engine, evaluation pipelines, model serving/tuning infrastructure, and monitoring systems. You will work closely with applied scientists and engineers to translate prototype agent capabilities into robust, scalable production systems. You will need to rapidly learn and apply new techniques in agent deployment, model tuning, reinforcement learning infrastructure, multi-step reasoning orchestration, and system optimization. You will build APIs, pipelines, and frameworks that allow agents to reason, plan, and act reliably at scale, ensuring low latency, high throughput, resilience, fault tolerance, versioning, and safety guardrails. A critical aspect of this role is being customer-obsessed: you will work backwards from advertiser needs to ensure that infrastructure decisions enable real customer-facing experiences. You will also partner with cross-functional teams—science, product, operations—to continuously iterate the agentic architecture, evaluation metrics, and tuning loops. This is a high-impact role where you balance deep technical craftsmanship with product sensibility, setting standards, influencing architecture, and owning end-to-end delivery of agentic capabilities.
Key job responsibilities
- Lead engineering strategy and roadmap for Sponsored Products Autonomous Campaigns
- Design and implement scalable architecture to host agent orchestration, tool invocation, state management, and feedback loops.
- Build scalable, reusable data and tool registry
- Construct evaluation pipelines (offline and online) to assess agent reasoning quality, performance metrics, safety constraints, and KPI impact.
- Integrate and manage tuning pipelines (e.g. hyperparameter tuning, RL fine-tuning, preference optimization), and provide abstraction layers for scientists to plug in models.
- Implement observability, logging, metrics, alerting, tracing, and drift detection for agent behaviors and model performance.
- Ensure resilience, fault isolation, auto-scaling, batching, caching, resource allocation, concurrency control, and SLA compliance.
- Rapidly prototype and evaluate new system designs or algorithmic patterns (e.g. streaming inference, memory caching, chaining of reasoning modules, tool embeddings).
- Collaborate in design reviews, code reviews, system design, and cross-team architecture alignment.
About the team
The Sponsored Products and Brands team at Amazon Ads is re-imagining the advertising landscape through the latest generative AI technologies, revolutionizing how millions of customers discover products and engage with brands across Amazon.com and beyond. We are at the forefront of re-inventing advertising experiences, bridging human creativity with artificial intelligence to transform every aspect of the advertising lifecycle from ad creation and optimization to performance analysis and customer insights.
We are a passionate group of innovators dedicated to developing responsible and intelligent AI technologies that balance the needs of advertisers, enhance the shopping experience, and strengthen the marketplace. If you're energized by solving complex challenges and pushing the boundaries of what's possible with AI, join us in shaping the future of advertising.
The Autonomous Campaigns team within Sponsored Products and Brands is focused on supporting 1.6MM advertisers to meet their advertising needs of creating and managing ad campaigns. At this scale, the complexity of diverse advertiser goals, campaign types, and market dynamics creates both a massive technical challenge and a transformative opportunity: even small improvements in auto campaign systems can have outsized impact on advertiser success and Amazon’s retail ecosystem.
Our vision is to build a highly personalized, context-aware agentic campaign creation and management system that leverages LLMs together with tools such as auction simulations, ML models, and optimization algorithms. This agentic framework, will operate across both chat and non-chat experiences in the ad console, scaling to natural language queries as well as proactively delivering guidance based on deep understanding of the advertiser. To execute this vision, we collaborate closely with stakeholders across Ad Console, Sales, and Marketing to identify opportunities—from high-level product guidance down to granular keyword recommendations—and deliver them through a tailored, personalized experience. Our work is grounded in state-of-the-art agent architectures, tool integration, reasoning frameworks, and model customization approaches (including tuning, MCP, and preference optimization), ensuring our systems are both scalable and adaptive.